Dynamical optimization of satellite structure based on multi-objective particle swarm optimization algorithm

被引：0

作者：

Xia, Hao ^{[1
]}

Chen, Chang-Ya ^{[2
]}

Wang, De-Yu ^{[1
]}

机构：

[1] State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai

[2] Shanghai Institute of Satellite Engineering, Shanghai

来源：

Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2015年 / 49卷 / 09期

关键词：

Dynamical optimization; Multi-objective optimization; Particle swarm optimization; Satellite;

D O I：

10.16183/j.cnki.jsjtu.2015.09.022

中图分类号：

学科分类号：

摘要：

Aimed at the multi-objective and dynamic optimization problem of satellite structure, a method called MOPSO was proposed. A strategy of decreasing the inertia weight was utilized, the particles that violated the constraints were punished respectively, and the mutation operator was introduced to enhance the diversity of swarms, giving this algorithm a better capability of global optimization. Combined with the support vector machine, MOPSO was applied to solve the multi-objective optimization problem of satellite structural dynamics. This approach obtained relatively better results compared with the results obtained by using the NSGA-II algorithm. Numerical results show that MOPSO can effectively and efficiently search and converge to the Pareto optimal front, which is dispersed and uniform. ©, 2015, Shanghai Jiao Tong University. All right reserved.

引用

页码：1400 / 1403and1410

共 9 条

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